. lort NESS 71
An Intercomparison of
Derived From Radiosonde and
Satellite Vertical Temperature
W. L. SMITH AND H.
NATIONAL OCEANIC AND
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NESC 38 Angular Distribution of Solar Radiation Reflected From Clouds as Determined From TIRHS IV Radi-
ometer Measurements. I. Ruff, R. Koffler, S. Fritz, J. S. Winston, and P. K. Rao, March 1967.
NESC 39 Motions in the Upper Troposphere as Revealed by Satellite Observed Cirrus Formations. H.
McClure Johnson, October 1966. (PR-173-996)
NESC 40 Cloud Measurements Using Aircraft Time-Lapse Photography. Linwood F. Whitney, Jr., and E. Paul
McClain, April 1967. (PB-174-728)
NESC 41 The SINAP Problem: Present Status and Future Prospects; Proceedings of a Conference Held at
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McClain, October 1967. (PB-176-570)
NESC 42 Operational Processing of Low Resolution Infrared (LRIR) Data From ESSA Satellites. Louis
Rubin, February 1968. (PB-178-123)
NESC 43 Atlas of World Maps of Long-Wave Radiation and Albedo--for Seasons and Months Based on Measure-
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NESC 45 The Nature of Intermediate-Scale Cloud Spirals. Linwood F. VJhitney, Jr., and Leroy D. Herman,
May 1968. (AD-673-681)
NESC 46 Monthly and Seasonal Mean Global Charts of Brightness From ESSA 3 and ESSA 5 Digitized Pic-
tures, February 1967-February 1968. V. Ray Taylor and Jay S. Winston, November 1968. (PB-180-
NESC 47 A Polynomial Representation of Carbon Dioxide and Water Vanor Transmission. William L. Smith,
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NESC 48 Statistical Estimation of the Atmosphere ' s Geopotential Height Distribution From Satellite
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NESC 49 Synoptic/Dynamic Diagnosis of a Developing Low- Level Cyclone and Its Satellite-Viewed Cloud
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50 Estimating Maximum Wind Speed of Tropical Storms From High Resolution Infrared Data. L. F.
Hubert, A. Timchalk, and S. Fritz, May 1969. (PR-184-611)
(Continued on inside back cover)
NOAA Technical Report NESS 71
An Intercomparison of
Derived From Radiosonde and
Satellite Vertical Temperature
W. L. SMITH AND H. M. WOOLF
DEPARTMENT OF COMMERCE
Frederick B. Dent, Secretary
NATIONAL OCEANIC AND
Robert M White. Administrator
David S Johnson. Director
'ent of '
I. Introduction 1
II. Discussion of results... 2
III. Conclusions 5
Acknowl edgments 5
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AN INTERCOMPARISON OF METEOROLOGICAL PARAMETERS
DERIVED FROM RADIOSONDE AND SATELLITE VERTICAL TEMPERATURE CROSS SECTIONS
W. L. Smith and H. M. Woolf
National Environmental Satellite Service, NOAA, Washington, D.C.
ABSTRACT. Vertical cross-sections of temperature between 60°S and
50°N for Apr. 6, 1973, are derived from (a) radiosonde, (b) Nimbus-5
Infrared Temperature Profile Radiometer, Nimbus-E Microwave Spectro-
meter and Selective Chopper Radiometer, and (c) NOAA-2 Vertical Temp-
erature Profile Radiometer (VTPR) data. Comparisons are made of the
level temperatures and latitudinal temperature gradients, geopoten-
tial heights and the latitudinal gradients, and geostrophic winds
inferred from the radiosonde and satellite cross-sections. The re-
sults of this limited case study indicate:
1. Temperature accuracies for the lower troposphere obtained with
Nimbus-5 sounding data are superior to those achieved with the NOAA-2
2. The agreement between latitudinal gradients of temperature de-
rived from satellite data and radiosonde observations is much better
than the agreement between level temperatures obtained from satellite
and radiosonde observations.
3. The geostrophic wind distribution of jet streams derived from
satellite data possesses more character and intensity than does the
geostrophic wind distribution obtained from radiosonde data.
Comparisons are made of vertical cross-sections of radiosonde, Nimbus-5, and NOAA-2 temper-
ature profiles that were observed at nearly the same time about a line extending from 60°S to
50°N on Apr. 6, 1973. Figure 1 shows the distribution of the radiosonde, Nimbus-5, and NOAA
Vertical Temperature Profile Radiometer (VTPR) data analyzed. The satellite profile obser-
vations selected were those that were geographically closest to the radiosonde stations. Since
the VTPR was spatially scanning, better space coincidence with the radiosonde observations was
All figures are grouped together at the back of the study.
achieved than with the suborbital track-restricted Nimbus-5 data. The more uniform north-
south distribution, however, of the Nimbus-5 data makes it more amenable to vertical cross-
section analysis than the radiosonde or VTPR data.
Figure 2 shows the north-south distributions of cloudiness in percentages reaching various
pressure levels, total precipitable water as derived from both the NEMS-microwave and the
ITPR-infrared data, and total outgoing longwave flux (langleys/day) as derived from the
Nimbus-5 radiance observations. Also shown is a pictorial image of the cloud distribution
obtained from the 4 n.mi. resolution scanning THIR aboard Nimbus 5. Note in the THIR cloud
photograph that there apparently are two jet streams (indicated by the cirrus streaks) cross-
ing the Nimbus orbital track, a subtropical jet near 25°N and a merging polar front jet near
35°N. As will be shown, the existence of these jet streams is verified by the thermal winds
derived from both the satellite and radiosonde data.
Before proceeding with a discussion of the results, it is important to point out certain
general features of the Nimbus-5 and NOAA-2 satellite temperature profile retrievals (for de-
tails, see Smith et al . 1974 and McMillin et al . 1973).
1. The NOAA-2 VTPR retrieval method uses the 12-hr forecast as an initial guess. The temp-
erature profile obtained using the "minimum information solution" (Fleming and Smith 1972) is
the minimum perturbation of the initial profile required to satisfy the outgoing radiance ob-
servations. As a result, vertical structure in the 12-hr forecast below the vertical resolu-
tion of the radiance observations is retained in the satellite profile retrieval.
2. The Nimbus-5 [ITPR + NEMS + SCR (Selective Chopper Radiometer)] retrieval system uti-
lizes regression equations relating temperature to radiances, generated from a cl imatological
sample of radiosonde data, to obtain the initial profile used in the minimum information so-
lution. Consequently, the Nimbus retrievals are independent of contemporary radiosonde or
3. Figure 1 shows that the Nimbus-5, NOAA-VTPR, and RAOB data geographically are not en-
tirely coincident. The most important systematic geographical discrepancy is north of 30°N
where the Nimbus data are located over China and the VTPR and radiosonde data are located
II. DISCUSSION OF RESULTS
Figures 3, 4, and 5 are cross sections of RAOB, Nimbus-5, and VTPR temperatures. Figures
6 and 7 show the difference of Nimbus-5 and VTPR retrievals with respect to the radiosonde
observations. In the troposphere, differences with the radiosonde (RAOB) are generally small
The Infrared Temperature Profile Radiometer (ITPR) on Nimbus 5 was designed with an east-
west scan capability. Owing to a scan mechanism malfunction, however, the ITPR was stopped
in the nadir-looking position during this orbit.
except around 25°N where +6°C (Nimbus-5) and +10°C (VTPR) differences occur. Looking at fig-
ure 1, however, we see that the RAOB location is 7° west of the Nimbus-5 and VTPR observations.
In the tropopause region, 300 to 100 mb, large differences of Nimbus-5 and RAOB observations
result from vertical resolution limitations of the satellite sensor. The VTPR-RAOB differ-
ences are smaller because of the good "first guess" used in the VTPR retrievals. This is ver-
ified by the differences, shown in figure 8, between the 12-hr forecast (used as the VTPR
first guess) and the RAOB. Since the Nimbus-5 retrievals do not use such contemporary first-
guess information, larger differences in the tropopause region are expected.
Note the vertical compensation of the errors. Probably, the most important feature illus-
trated in figures 6 and 7 is that the errors (or differences) are spatially correlated so that
one would expect smaller differences between the spatial gradients than between the point
Figure 9 shows comparisons of the horizontal gradients, over 3° of latitude, at isobaric
levels of temperatures derived from the RAOB and Nimbus-5 soundings. There is \jery good cor-
respondence between the two fields of temperature gradients. The differences are probably
within the noise level expected to exist between two RAOBs spaced 3° of latitude apart and
those due to the different locations of the RAOB and the Nimbus-5 data.
Figure 10 shows comparisons of the geostrophic wind derived from the Nimbus-5 and RAOB temp-
erature cross-sections. The overall agreement of the distribution of wind associated with
the jet streams is quite good. This experimental result confirms the theoretical study pre-
sented by Togstad and Horn (1974). The different location of the wind maximum is probably a
result of the different longitudinal orientation of the RAOB and Nimbus-5 data (see fig. 1).
The fact that the Nimbus-5 pattern displays more character and stronger maximum winds is prob-
ably because of the higher density of Nimbus-5 soundings.
Figures 11 through 14 present various statistics obtained from the entire 60°S to 50°N cross-
sections. Part (a) of each figure shows the standard deviations between the radiosonde pro-
files and those obtained from the dynamical forecast (i.e., the initial profile used in the
VTPR solution), the VTPR soundings, and the Nimbus-5 soundings. Part (b) of each figure shows
the correlation of the differences between the satellite soundings and the radiosonde obser-
vations with the differences between the forecast soundings and the radiosonde observations.
Finally, part (c) shows the minimum standard deviation expected between the radiosonde obser-
vations and an analysis constructed by updating the forecast with the satellite soundings.
This analysis procedure, initially suggested by Bonner (1974), consists of prescribing the
analyzed temperature at each level as a linear combination of the forecast temperature and
the satellite-derived temperature. The weighting coefficient of this linear equation is ob-
tained through a minimization procedure. Its numerical value is a function of the expected
standard errors of the forecast and the satellite retrieval, as well as the expected corre-
lation of forecast and satellite profile errors. (In this analysis, the radiosonde observa-
tions are taken as "truth" in computing these statistically expected values.)
Since here the weighting coefficient has been defined in an optimum way, using "the radio-
sonde truth" for its determination, the final analysis result is bound to be more accurate
than either the forecast or satellite value. Although an optimum weighting coefficient can-
not be defined in practice (since "truth" is always unknown), this analysis procedure is still
a convenient way of illustrating the added information content of the satellite soundings over
that already contained in the dynamical forecast.
In figure 11(a), we see that, below the 500-mb level, the Nimbus data agree much better with
the radiosonde data than do the VTPR observations. This result most likely is due to the sup-
erior ability of the Nimbus-5 sounders to probe into, between, and through clouds. (The
Nimbus-5 ITPR has four times the area resolution of the NOAA-2 VTPR, and the Nimbus-5 NEMS
microwave instrument is able to probe directly through clouds.) In the tropopause region,
however, the Nimbus-5 soundings are inferior to the VTPR profiles. The superiority of the
VTPR profiles probably is a result of the incorporation of the 12-hr forecast in the solution.
Evidence of this is given in the correlation coefficient profiles in part (b). We see that,
in the upper troposphere, the error of the VTPR retrieval is highly correlated with the error
of the 12-hr forecast, indicating that the forecast has a dramatic influence on the VTPR pro-
fi le result.
Note the high correlations of the error of the forecast-independent Nimbus-5 retrievals
and the error of the forecast in the surface layer below 700 mb and in the 200- to 500-mb
region. This apparently is due to the fact that both the forecast profiles and Nimbus-5 sat-
ellite profiles tend to smooth through fine-scale vertical structures such as surface and
tropopause inversions. Consequently, since both the forecast and satellite retrievals re-
solve a similar vertical scale which is larger than that resolved by the radiosonde, a high
correlation results in regions where fine-scale structure exists. The fact that the VTPR
error is slightly less correlated than the Nimbus-5 error in the lower troposphere probably
is a result of cloud noise.
Combining the satellite data with the 12-hr forecast using optimum weights yields the anal-
ysis result shown in figure 11(c). Note that the most dramatic influence of the satellite
data is above the 700-mb level for both the Nimbus-5 and VTPR retrieval cases. The minor
influence below 700 mb is a result of the relatively high error correlations (the vertical
scale correlation discussed above) and the fact that the forecast profiles are relatively
accurate. Remember, however, that the forecast probably is unrepresentatively accurate for
this case since the cross-section area is within, and downstream of, a dense network of radio-
sonde data. Also note that the large differences between the Nimbus-5 and VTPR standard dev-
iations with radiosondes are diminished greatly when the retrievals are combined with the
12-hr forecast using optimum weights to produce the analysis result. This result suggests
that the differences between the two satellite profiles shown in figure 11(a) mainly are due
to the differences in the initial profile used in the retrieval process and not to the infor-
mation content of the radiance observations. The differences in information content of the
two satellite sounding systems are reflected more accurately in figure 11(c).
Figures 12, 13, and 14 show similar statistical results for temperature gradients, geopo-
tential heights, and geostrophic winds. In viewing the standard deviation portions (a) of
each figure, we note that the satellite results are generally inferior to the relatively ac-
curate 12 hr forecast results. Portion (c), however, of each figure reveals that the satel-
lite data, when added to the forecast profiles to construct an analysis, leads to a signifi-
cant reduction of the error of the forecast although that error is relatively small (in this
case). Of course, one would expect to see an even more dramatic impact of the satellite data
in situations where the forecast error is much larger, which is more likely to be the case in
areas where radiosonde data are sparse.
This limited case study has revealed the following characteristics of the Nimbus-5 and VTPR
temperature retrieval data:
1. Much better agreement exists between temperature gradients derived from Nimbus-5, VTPR,
and radiosonde data than between the absolute temperatures. (Compare figs. 11 and 12.) This
indicates that the satellite retrievals possess large horizontal scale bias errors that could
be caused by (a) biases in the initial data used in the retrieval process (i.e., statistical
or dynamical forecast data), (b) biases caused by aerosols or undetected large-scale cloudi-
ness, or (c) systematic errors in the weighting functions.
2. The geostrophic wind distribution associated with intense baroclinic phenomena (e.g.,
the jet stream) can be diagnosed accurately from the satellite temperature retrieval data.
The results shown here indicate that the Nimbus-5 results may even be superior to radiosonde
results, suggesting that the thermal gradients obtained from the closely spaced Nimbus data
are more accurate than those obtained from the more coarsely spaced radiosonde observations.
3. Even in regions where the forecast is relatively accurate, such as the case investigated
here, the satellite retrieval data are sufficiently independent to provide an analysis with
an accuracy superior to that of the forecast.
The authors appreciate the contributions of L. Mannello and P. Pellegrino who plotted and
analyzed the cross sections and prepared the data for computer processing.
Bonner, William D. (National Meteorological Center, National Weather Service, U.S. Depart-
ment of Commerce, Washington, D.C.), "An Analysis Procedure Constructed by Updating a
Forecast With Satellite Soundings," 1974 (unpublished memorandum).
Fleming, H. E., and Smith, W. L., "Inversion Techniques for Remote Sensing of Atmospheric
Temperature Profiles," Temperature , Its Measurement and Control in Science and Industry ,
Vol. 4, Part 3, Instrument Society of America, Pittsburgh, Pa., Apr. 1972, pp. 2239-2250.
McMillin, L. M., Wark, D. Q., Siomkajlo, J. M., Abel, P. G., Werbowetzki, A., Lauritson, L. A.,
Pritchard, J. A., Crosby, D. S., Woolf, H. M., Luebbe, R. C, Weinreb, M. P., Fleming, H. E.,
Bittner, F. E., and Hayden, C. M., "Satellite Infrared Soundings From NOAA Spacecraft,"
NOAA Technical Report NESS 65, National Environmental Satellite Service, National Oceanic
and Atmospheric Administration, U.S. Department of Commerce, Washington, D.C., Sept. 1973,
Smith, W. L., Woolf, H. M. , Abel, P. G., Hayden, C. M., Chalfant, M., and Grody, N., "Nimbus-5
Sounder Data Processing System; Part I: Measurement Characteristics and Data Reduction Pro-
cedures," NOAA Technical Memorandum NESS 57, National Environmental Satellite Service, Na-
tional Oceanic and Atmospheric Administration, U.S. Department of Commerce, Washington, D.C.,
June 1974, 99 pp.
Togstad, William E., and Horn, Lyle H., "An Application of the Satellite Indirect Sounding
Technique in Describing the Hyperbaroclinic Zone of a Jet Streak," Journal of Applied Met -
eorology , Vol. 13, No. 2, Mar. 1974, pp. 264-276.
Figure 1 .--Geographical locations of radiosonde,
Nimbus-5, and NOAA VTPR soundings. UT, Universal
Time, is equivalent to GMT, Greenwich Meridian
April 6, 1973 _
(0121-0204 U T)
otal H 2 U vapor
Total H 2 Vapor (NEMS)
-o o Total H 2 Vapor (RAOB)
Figure 2. --Latitude cross-section of total integrated water vapor (g/cm ), total outgoing
longwave flux (langleys/day) , amount (%) of cloudiness reaching various pressure levels
(derived from the Nimbus-5 radiance measurements). The cloud image obtained from the
Nimbus-5 Temperature Humidity Infrared Radiometer (THIR) appears at the top. NEMS re-
presents Nimbus-E Microwave Spectrometer, and RAOB represents Radiosonde Observation.
60S | 40S
Latitude - Longitude (°)
Figure 3. --Vertical cross-section of radiosonde temperature obser-
vations (°C) on Apr. 6, 1973, at 0000 GMT
170E165E 160E 155E 150E U5E UOE 135E130E125E
Latitude -Longitude (°)
Figure 4. --Vertical cross-section of Nimbus-5 temperature obser-
vations (°C) on Apr. 6, 1973, at 0121 to 0204 GMT
40N | 60N
Latitude - Longitude (°)
Figure 5. --Vertical cross-section of NOAA-2 VTPR temperature observations (°C)
on Apr. 5, 1973, at 2023 to 2355 GMT
50N 40 30 20 ION EQ 10S 20 30 40 50 60S
Figure 6. --Difference (°C) between the Nimbus-5 and radiosonde tempera-
ture cross-section analyses
Figure 7. --Difference (°C) between the VTPR and radiosonde temperature cross-section analyse:
Figure 8. --Difference (°C) between the 12-hr forecast and radiosonde temperature cross-sectio
Figure 9. --Radiosonde and Nimbus-5 temperature gradients over 3'
latitude obtained from the cross-section analyses
Figure 10.--Geostrophic (integrated thermal) winds (m/s) computed
from the radiosonde and Nimbus-5 temperature cross-sections
Forecast - RAOB
VTPR - RAOB
NIMBUS 5 - RAOB
Figure 11. --(a) Standard deviations of temperature (°C) obtained
from the radiosonde cross-section analyses and the cross-section
analyses of (1) 12-hr forecast (short dashes), (2) the VTPR (long
dashes), and (3) the Nimbus-5 (solid curve); (b) correlation of
the differences between the cross-section analyses for the fore-
cast and radiosonde temperature data with (1) the differences be-
tween the cross-section analyses for the VTPR and radiosonde
temperature data (dashed curve) and (2) the differences between
the cross-section analyses for the Nimbus-5 and radiosonde temp-
erature data (solid curve); and (c) expected standard deviations
of the cross-section analysis of radiosonde temperature data
with an "optimum" analysis of (1) forecast data (short dashes),
(2) VTPR data (long dashes), and (3) Nimbus-5 data (solid curve)
Forecast - RAOB
VTPR - RAOB
NIMBUS 5 -RAOB
05 1.0 1.5 2.0 2.5
0.5 1.0 1.5 2.0 2.5
Figure 12. --Same as figure 11 except here it is for temperature
gradients (°C) over 3° of latitude
Forecast - RAOB
VTPR - RAOB
NIMBUS 5 - RAOB
80 100 120
Figure 13. --Same as figure 11 except here 1t is for geopotential height (m)
Forecast - RAOB
VTPR - RAOB
NIMBUS 5 - RAOB
5 10 15 20 25 30 -1 1 5 10 15 20 25
Figure 14.— Same as figure 11 except here it is for geostrophic wind (m/s)
(Continued from inside front cover)
NESC 51 Application of Meteorological Satellite Data in Analysis and Forecasting. Ralph K. Anderson,
Jerome P. Ashman, Fred Bittner, Golden R. Farr, Edward W. Ferguson, Vincent J. Oliver, and
Arthur H. Smith, September 1969 (AD-697-033) . Supplement (AD-740-017) .
NESC 52 Data Reduction Processes for Spinning Flat-Plate Satellite-Borne Radiometers. Torrence H.
MacDonald, July 1970. (COM-71-00132)
NESC 53 Archiving and Climatological Applications of Meteorological Satellite Data. John A. Leese,
Arthur L. Booth, and Frederick A. Godshall, July 1970. (COM-71-00076)
NESC 54 Estimating Cloud Amount and Height From Satellite Infrared Radiation Data. P. Krishna Rao,
July 1970. (PB-194-685)
NESC 56 Time-Longitude Sections of Tropical Cloudiness (December 1966-November 1967). J. M. Wallace,
July 1970. (COM-71-00131)
NOAA Technical Reports
NESS 55 The Use of Satellite-Observed Cloud Patterns in Northern Hemisphere 500-mb Numerical Analysis.
Roland E. Nagle and Christopher M. Hayden, April 1971. (COM-73-50262)
NESS 57 Table of Scattering Function of Infrared Radiation for Water Clouds. Giichi Yamamoto,
Masayuki Tanaka, and Shoji Asano, April 1971. (COM-71-50312)
NESS 58 The Airborne ITPR Brassboard Experiment. W. L. Smith, D. T. Hilleary, E. C. Baldwin, W. Jacob,
H. Jacobowitz, G. Nelson, S. Soules, and D. 0. Wark, March 1972. (COM-72-105S7)
NESS 59 Temperature Sounding From Satellites. S. Fritz, D. 0. Wark, H. E. Fleming, W. L. Smith, H.
Jacobowitz, D. T. Hilleary, and J. C. Alishouse, Julv 1972. (COM-72-50963)
NESS 60 Satellite Measurements of Aerosol Backscattered Radiation From the Nimbus F Earth Radiation Ex-
periment. H. Jacobowitz, W. L. Smith, and A. J. Drummond, August 1972. (COM-72-51031)
NESS 61 The Measurement of Atmospheric Transmittance From Sun and Sky With an Infrared Vertical
Sounder. W. L. Smith and H. B. Howell, September 1972. (COM-73-50020)
NESS 62 Proposed Calibration Target for the Visible Channel of a Satellite Radiometer. K. L. Coulson
and H. Jacobowitz, October 1972. (COM-73-10143)
NESS 63 Verification of Operational SIRS B Temperature Retrievals. Harold J. Brodrick and Christopher
M. Hayden, December 1972. (COM-73-50279)
NESS 64 Radiometric Techniques for Observing the Atmosphere From Aircraft. William L. Smith and Warren
J. Jacob. January 1973. (OT1-73-50376)
NESS 65 Satellite Infrared Soundings From NOAA Spacecraft. L. M. McMillin, D. 0. Wark, J.M. Siomkailo,
P. G. Abel, A. Werbowetzki, L. A. Lauritson, J. A. Pritchard, D. S. Crosby, H. M. Woolf, R. C.
Luebbe, M. P. Weinreb, H. E. Fleming, F. E. Bittner, and C. M. Hayden, September 1973. (C0M-
NESS 66 Effects of Aerosols on the Determination of the Temperature of the Earth's Surface From Radi-
ance Measurements at 11.2 ym. H. Jacobowitz and K. L. Coulson, September 1973. (COM- 74-50013)
NESS 67 Vertical Resolution of Temperature Profiles for High Resolution Infrared Radiation Sounder
(HIRS). Y. M. Chen, H. ?!. Woolf, and W. L. Smith, January 1974. (COM-74-50230)
NESS 68 Dependence of Antenna Temperature on the Polarization of Emitted Radiation for a Scanning Mi-
crowave Radiometer. Norman C. Grody, January 1974. (COM-74-50431/AS)
NESS 69 An Evaluation of May 1971 Satellite-Derived Sea Surface Temperatures for the Southern
Hemisphere. P. Krishna Rao, April 1974. (COM-74-50643/AS)
NESS 70 Compatibility of Low-Cloud Vectors and Rawins for Synoptic Scale Analysis. L. F. Hubert and L.
F. Whitney, Jr., October 1974.
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